How Cloud Finance Works

    Let's talk about how one of the main components of a cloud company is arranged - finance.

    A few simple metrics - MRR , CLV , CAC - help evaluate the company's economy . In this post we will talk about how to count and interpret them.

    MRR: how to measure business growth

    The main feature of a cloud company is that it sells a service, not a license. In practice, this means that customers pay access to the subscription solution, usually on a monthly basis.



    From a financial point of view, this is an advantage. We are well insured against seasonality of sales - most clients work all year long. Monthly Recurring Revenue ( MRR ) can be calculated using a simple formula:

    MRR = ARPU * number of customers

    ARPU - average monthly customer payment. If your service has only one paid tariff, then ARPU, of course, will be equal to its cost. The tariff fork of our service is quite large - from 400 to 6,400 rubles, and the average payment is approximately equal to 2,000 rubles.

    The MRR figure makes it possible to understand how fast the business is growing. I will explain this in more detail: it seems that the easiest way is to look at the amount of customer payments. If in June we received more payments than in May, then everything is fine - we are growing. Actually, this is not so.

    Current payments are very much influenced by various incentive measures for customers, for example, promotions. A good offer, such as “pay for the year - get a discount”, can greatly increase current payments. But this does not mean business growth - with the help of the action, we simply stimulated customers to transfer their future payments to this month.

    If we calculated the MRR and saw that it had grown by 10% in a month, this would be a completely objective comparison.

    CLV: how long does your client live?

    MRR shows us the payment of all customers for one month. Now let's calculate how much one client pays for the entire period of his “life”.

    Customers remain customers as long as they pay for their subscription. You must understand that customers do not use the service forever. They close projects for which automation was needed, switch to other products, and finally just leave the business.

    The average life time of a client can be most accurately measured by the monthly outflow from the entire client base. For example, if the outflow per month is 5%, the client's lifetime is 1 / 0.05 = 20 months.

    Knowing this number, you can calculate another important metric - CLV (Customer Lifetime Value). This is the profit that your average client will bring during the entire period of work.

    CLV = (ARPU - expenses) * average client’s “life” time

    For a cloud service, the costs in this formula are the cost of support (employee salaries, telephone communications, document management with legal entities) and technical infrastructure (servers and their maintenance). At low tariffs, even such seemingly insignificant expenses as postage - sending closing documents for bookkeeping - can significantly reduce LTV.

    In a first approximation, it is enough to consider the CLV “hospital average”. But such an average is not very useful. Customers must be divided into groups. As a rule, the cloud service already has a ready segmentation - at the tariffs.

    Customer segmentation may produce unexpected results. For example, the cost of our two tariffs differs by 6 times, but the CLV of customers at these tariffs is already 28 times (!). This is due to the fact that users of a more expensive tariff work with the service for much longer.

    CAC: how much is the client?

    CLV alone is not of great value. However, by measuring CLV, you can meaningfully plan the costs of attracting new customers. The costs consist of the cost of advertising, expenses for events, salaries, bonuses of sellers and marketers, and so on. This metric is called CAC - Customer Acquisition Cost. In a first approximation, you can simply divide the monthly budget of the marketing and sales department by the number of new customers for the same period.
    It is clear that the company cannot spend more money on attracting a new client than it will subsequently receive from it. Such a model will lead the business to disaster. In practice, no more than one third of the client’s value is considered a good indicator for the cost of attraction.

    CAC <CLV / 3

    Just like CLV, CAC needs to be segmented. For example, we consider CAC in separate channels (context / SEO / social networks) and separate campaigns in context. As a result, we can manage the budget of individual campaigns based on statistics, rather than our guesses.

    Financial plan: company control panel

    The listed metrics are useful in their own right. But most importantly, they can be used to carry out realistic planning.

    Its main task is to draw up a financial plan, that is, a schedule for revenue and expenses. This allows you to predict cash flow , that is, the amount of money in the company's current account.

    The basis of revenue planning is the MRR metric, which we talked about above. This is the amount of payments that the company will receive every month. MRR depends on the ARPU and the current number of customers, so in fact the plan is based on these two indicators.

    The cost of attracting a new customer - CAC - is usually higher than its first payment. In fact, each new client is unprofitable at the beginning, and only after 2, 3 or more months it pays off and, finally, begins to make a profit. The financial plan takes this effect into account and shows in advance cash flow problems if they can occur.

    In our company, a monthly budget is drawn up at the beginning of the year. These figures are fixed, and each month are compared with the fact. As a result, we know whether the company is working better or worse than the plan and, if necessary, we are promptly making changes.

    In this post, we wanted to share tools for analyzing and managing the finances of a cloud company. We hope that they will help you in the same way as they help us to develop the MySklad service .

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